TY - CONF A1 - Gornushkin, Igor B. T1 - Importance of Spectral Resolution for Accurate Plasma Diagnostics with Implications for Calibration-Free LIBS N2 - In the LIBS literature, almost every second article reports the determination of the plasma temperature using the Boltzmann plot method or the determination of the electron density using the Stark line broadening relation. The first requires the measurement of the integrated intensities of the spectral lines, and the second requires the measurement of the linewidth, under the same assumption of optical thinness. It is taken for granted that this can be easily done either by working with the raw spectra or by fitting an appropriate function to the observed spectral lines. As a rule, reported data are not verified either by an alternative method (e.g., Thomson scattering) or by computer simulations using synthetic spectra. However, the question of how to extract the necessary information from the raw spectral data is not as simple as it might seem. The quality of such an extraction will depend critically on the type of spectral instrument used, its resolution, and the noise superimposed on the data. The problem is that we do not see the spectrum emitted by the plasma, but the spectrum distorted by the measurement; an exaggerated example of such a distortion is shown in Fig. 1. The elimination of this distortion belongs to the class of inverse problems, the so-called ill-posed problems, whose successful solution crucially depends on the quality of the information available. When it comes to spectroscopy, quality of information primarily means high spectral resolution and low noise. Not all spectrometers used in LIBS can provide the quality needed to solve the inverse problem; this casts doubt on many published plasma measurements. The current presentation will be devoted to general shortcomings in the processing of spectral data and inaccuracies in the determination of plasma parameters resulting from these shortcomings. The analysis is based on the use of synthetic spectra produced by plasma with known characteristics, i.e., temperature, species densities, and electron density. The estimation of errors caused by inadequate processing of spectral data is made by comparing the initial and reconstructed plasma parameters. Recipes will be given for which the analytic function best approximates the observed spectral lines, and how data processing errors affect accuracy of calibration-free LIBS will be discussed. These issues were only partially covered in previously published works, for example [1, 2, 3]. T2 - EMS LIBS 2023 CY - Porto, Portugal DA - 04.09.2023 KW - Laser induced breakdown spectroscopy KW - Calibration-free analysis KW - Data processing PY - 2023 AN - OPUS4-58590 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Gornushkin, Igor B. T1 - Improved Data Processing for Accurate Plasma Diagnostics and Calibration-Free LIBS N2 - Many applications of LIBS require the measurement of plasma temperature and electron density, which in turn requires knowledge of the integrated line intensity and the shape of the spectral lines. While the integral intensity is preserved as light passes through the spectrometer, the shape emitted by an individual atom or ion is greatly distorted. This is due, firstly, to the transfer of light through the plasma (self-absorption), secondly, to the influence of the instrumental function of the spectrometer, and, thirdly, to the aberrations of the optical system. In addition, processing of spectral information, such as background removal, noise reduction, deconvolution, and line fitting, introduces additional errors in the reconstructed linewidth and line integral, which leads to erroneous temperature and electron density values. This communication will be devoted to the general shortcomings of spectral data processing and the resulting inaccuracies in determining the plasma parameters. The analysis is based on the use of synthetic spectra generated by plasma with known temperature and particle density. The estimation of errors caused by inadequate processing of the spectral data is made by comparing the initial and determined plasma parameters. As a result, an improved data processing method will be proposed that takes into account the spectrum distortion by the instrumental function and integration on the pixel detector. The former is accounted for by convolution (instead of deconvolution) of the estimated line profile using a predetermined slit function, and the latter is achieved by piecewise integration of the line profile by the pixel detector, taking into account the pixel size and uniform or non-uniform pixel separation. Recommendations will be made for which analytic function best approximates the observed spectral lines and examples will be given for the application of this routine to calibration-free LIBS using both synthetic and experimental data. T2 - SciX 2023 CY - Sparks, USA DA - 08.10.2023 KW - Laser induced plasma KW - Calibration-free analysis KW - Plasma modeling KW - Emission spectroscopy PY - 2023 AN - OPUS4-58591 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Gornushkin, Igor B. A1 - Mendez, Cristina A1 - Bordel, Nerea T1 - Investigation of LIBS-RF Plasma for Analytical Spectroscopy N2 - Laser breakdown spectroscopy (LIBS) is a common tool for applications in various fields of science and technology. Originally an atomic analysis technique, LIBS was later extended to molecular analysis due to the transient nature of the laser-induced plasma, which develops from a hot dissociation stage on a nanosecond to several microsecond scale to a relatively cold recombination stage on a scale of 10 to 100 microseconds after breakdown. Molecules formed during the recombination stage or incompletely dissociated after ablation can be efficiently detected, allowing the analysis of "difficult" elements or even molecular isotopes. However, with a small amount of ablated material and a short lifetime of the luminous plasma, analytical signals, especially molecular ones, can be very weak. Several methods have been proposed for reheating the plasma and increasing its lifetime, for example, a two-pulse LIBS or a LIBS combined with microwave radiation or with an electric spark discharge. Here we propose another one, LIBS combined with a capacitively coupled RF discharge at 13.6 MHz. The advantages of this combination are an increase in the lifetime of atomic and molecular emission and operation in a low-pressure atmosphere, which significantly reduces pressure line broadening and allows high-resolution spectroscopy. Another major advantage is operating in a chemically controlled atmosphere that can predictably drive desired chemical reactions. In this presentation, we will show the first results obtained with RF-LIBS combination. These will include separate and joint characterization of LIBS and RF plasmas and evaluation of its potential for elemental and molecular analysis and for plasma enhanced chemical vapor deposition. T2 - SciX 2023 CY - Sparks, USA DA - 08.10.2023 KW - Laser induced breakdown spectroscopy KW - Capacitively coupled discharge KW - RF-LIBS combination KW - Plasma reheating PY - 2023 AN - OPUS4-58592 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Gornushkin, Igor B. T1 - Modeling laser-induced plasma in vacuum and low-pressure co2 atmosphere N2 - The aim of the project is to develop an adequate model of laser induced plasma for conditions expected in space missions, i.e., vacuum, or low-pressure CO2 atmosphere. Numerical modeling will help to find optimal experimental parameters for the laser ablation under artificial lunar or Martian environments and obtain both qualitative, in terms of a composition, and quantitative, in terms of an elemental abundance, information about interrogated samples based on spectral data generated by the model. The best operational conditions will be found at a low cost without conducting tedious and time-consuming optimization experiments. The modeling approaches will be supported by machine learning to accelerate the optimization. T2 - Workshop on DFG project CY - Brno, Czech Republic DA - 10.08.2023 KW - Laser induced plasma KW - CFD computational fluid dynamic KW - Plasma modeling PY - 2023 AN - OPUS4-58595 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Küttenbaum, Stefan T1 - Guideline on NDT-supported reliability assessment of existing structures N2 - The presentation summarizes the idea and the methodology of the ZfPStatik project and gives insight into three case studies, showing how non-destructive testing results can be utilized beneficially in the recalculation of existing prestressed concrete and reinforced concrete bridges. T2 - 2nd Conference of the European Association on Quality Control of Bridges and Structures – EUROSTRUCT2023 CY - Vienna, Austria DA - 26.09.2023 KW - Reliability KW - Assessment KW - Existing structures KW - Non-destructive testing PY - 2023 AN - OPUS4-58485 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bayerlein, Bernd T1 - Platform MaterialDigital Core Ontology (PMDco): A Community Driven Mid-Level Ontology in the MSE Domain N2 - Knowledge representation in the materials science and engineering (MSE) domain is a vast and multi-faceted challenge: Overlap, ambiguity, and inconsistency in terminology are common. Invariant and variant knowledge are difficult to align cross-domain. Generic top-level semantic terminology often is too abstract, while MSE domain terminology often is too specific. The PMDco is designed in direct support of the FAIR principles to address immediate needs of the global experts community and their requirements. The illustrated findings show how the PMDco bridges semantic gaps between high-level, MSE-specific, and other science domain semantics, how the PMDco lowers development and integration thresholds, and how to fuel it from real-world data sources ranging from manually conducted experiments and simulations as well as continuously automated industrial applications. T2 - Patents4Science CY - Berlin, Germany DA - 05.10.2023 KW - Knowledge Representation KW - Semantic Interoperability KW - FAIR data management KW - Knowledge graph and ontologies KW - PMD Core Ontology PY - 2023 AN - OPUS4-58507 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Simon, Fabian T1 - HR-CS-GFMAS a new screening tool for per- and polyfluoroalkyl substances (PFAS) in the environment N2 - Per- and polyfluorinated alkyl substances (PFASs) are a large group of anthropogenic contaminates. Concerning are especially their persistent, bioaccumulative and toxic properties. Mostly, target-based approaches (e.g., LC-MS/MS) are utilized for the analysis of PFASs in the environment. But these approaches are limited to the availability of analytical grade standards and therefore drastically underestimate the total PFAS burden. Analytical approaches based on total fluorine for PFAS sum parameter analysis become increasingly important to indicate realistic PFAS pollution levels. PFAS sum parameters display the proportion of organically bound fluorine that can either be extracted (EOF) or adsorbed to activated carbon (AOF). For the instrumental analysis of such sum parameters, a fluorine selective detector is needed. Besides combustion ion chromatography (CIC), high resolution-continuum source-graphite furnace molecular absorption spectrometry (HR-CS-GFMAS) is a sensitive and highly selective tool for fluorine determination. The method is based on the in situ formation of diatomic gallium-mono fluoride (GaF) in a graphite furnace at a temperature of 1550°C. The molecular absorption of GaF can be detected at its most sensitive wavelength at 211.248 nm providing limits of quantification in the low µg F L-1 range. Here, we present a comparison of total fluorine analysis methods – AOF vs. EOF and HR-CS-GFMAS vs. CIC. Therefore, surface water samples from the Spree River in Berlin, Germany were analyzed at 10 locations for total fluorine (TF), AOF and EOF. The AOF made up 0.14–0.81% of TF and the EOF 0.04–0.28% of TF while AOF concentrations were systematically higher. For the instrumental comparison, HR-CS-GFMAS was the more sensitive and precise method for fluorine analysis compared to CIC. T2 - ICOBTE / ICHMET 2023 CY - Wuppertal, Germany DA - 06.09.2023 KW - PFAS KW - HR-CS-GFMAS KW - Fluorine KW - WWTP KW - SPE PY - 2023 AN - OPUS4-58245 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Bayerlein, Bernd T1 - News from the working area - Semantic Interoperability N2 - This presentation provides a comprehensive overview of recent developments and the current status within the Semantic Interoperability work area, with a particular emphasis on the advancements related to the Platform MaterialDigital Core Ontology (PMDco). The presentation will delve into the collaborative and community-supported curation process that has been instrumental in shaping PMDco. Additionally, we will introduce the innovative Ontology Playground, showcasing its role in fostering experimentation and exploration within the realm of ontology development. T2 - MaterialDigital Vollversammlung CY - Karlsruhe, Germany DA - 21.09.2023 KW - Semantic Representation KW - FAIR data management KW - Semantic Interoperability KW - Knowledge graph and ontologies KW - PMD Core Ontology KW - MaterialDigital PY - 2023 AN - OPUS4-58422 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Klewe, Tim T1 - LIBS ConSort: Development of a sensor-based sorting method for constuction and demolition waste N2 - Closed material cycles and unmixed material fractions are required to achieve high recovery and recycling rates in the building industry. In construction and demolition waste (CDW) recycling, the preference to date has been to apply simple but proven techniques to process large quantities of construction rubble in a short time. This is in contrast to the increasingly complex composite materials and structures in the mineral building materials industry. Manual sorting involves many risks and dangers for the executing staff and is merely based on obvious, visually detectable differences for separation. An automated, sensor-based sorting of these building materials could complement or replace this practice to improve processing speed, recycling rates, sorting quality, and prevailing health conditions. A joint project of partners from industry and research institutions approaches this task by investigating and testing the combination of laser-induced breakdown spectroscopy (LIBS) with near-infrared (NIR) spectroscopy and visual imaging. Joint processing of information (data fusion) is expected to significantly improve the sorting quality of various materials like concrete, main masonry building materials, organic components, etc., and may enable the detection and separation of impurities such as SO3-cotaining building materials (gypsum, aerated concrete, etc.) Focusing on Berlin as an example, the entire value chain will be analyzed to minimize economic / technological barriers and obstacles at the cluster level and to sustainably increase recovery and recycling rates. We present current advances and results about the test stand development combining LIBS with NIR spectroscopy and visual imaging. In the future, this laboratory prototype will serve as a fully automated measurement setup to allow real-time classification of CDW on a conveyor belt. T2 - 21. International Conference on Building Materials (Ibausil) CY - Weimar, Germany DA - 13.09.2023 KW - Material classification KW - Data fusion KW - Circular economy KW - LIBS KW - Recycling PY - 2023 AN - OPUS4-58495 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Friedrich, Alexander T1 - The AIFRI Project - Artificial Intelligence For Rail Inspection N2 - The rails of modern railways face an enormous wear and tear from ever increasing train speeds and loads. This necessitates diligent non-destructive testing for defects of the entire railway system. Non-destructive testing of rail tracks is carried out by rail inspection trains equipped with ultrasonic and eddy current test devices. However, the evaluation of the gathered data is mainly done manually with a strong focus on ultrasonic data, and defects are checked on-site using hand-held testing equipment. Maintenance measures are derived based on these on-site findings. The aim of the AIFRI project (Artificial Intelligence For Rail Inspection) is to - increase the degree of automation of the inspection process, from the evaluation of the data to the planning of maintenance measures, - increase the accuracy of defect detection, - automatically classify detected indications into risk classes. These aims will be achieved by training a neural network for defect detection and classification. Since the current testing data is unbalanced, insufficiently labeled and largely unverified we will supplement fused, simulated eddy current and ultrasonic testing data in form of a configurable digital twin. T2 - PostDoc Day 2022 CY - Berlin, Germany DA - 03.11.2022 KW - Non-destructive testing KW - Artificial intelligence KW - Simulation KW - Eddy current KW - Ultrasound PY - 2022 AN - OPUS4-57240 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -